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FOCS
2005
IEEE
15 years 10 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
143
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DAGSTUHL
2007
15 years 6 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
NETWORKS
2006
15 years 4 months ago
Approximation algorithms for channel allocation problems in broadcast networks
We study two packing problems that arise in the area of dissemination-based information systems; a second theme is the study of distributed approximation algorithms. The problems c...
Rajiv Gandhi, Samir Khuller, Aravind Srinivasan, N...
COCOON
2007
Springer
15 years 11 months ago
Distributed Approximation Algorithms for Weighted Problems in Minor-Closed Families
We give efficient distributed approximation algorithms for weighted versions of the maximum matching problem and the minimum dominating set problem for graphs from minor-closed fam...
Andrzej Czygrinow, Michal Hanckowiak
ORL
2007
47views more  ORL 2007»
15 years 4 months ago
A simpler and better derandomization of an approximation algorithm for single source rent-or-buy
We present a very simple way of derandomizing the algorithm proposed by Gupta, Kumar and Roughgarden for Single Source Rent-or-Buy by using the method of conditional expectation. ...
David P. Williamson, Anke van Zuylen